Most digital cameras now have the capability of capturing several images in rapid succession. Thus, such cameras can be used to obtain a sequence of images of a moving object (e.g., an automobile) traveling through a particular scene (e.g., a segment of a roadway).
Existing digital image processing systems attempt to process a sequence of images in order to create a visual effect connoting motion. For example, after capturing a time sequence of digital photographic images, some systems attempt to generate a new photorealistic image in which blurring is applied either to the moving object or to the entire image (moving object and background) in order to give the appearance of motion.
Other systems attempt to use computer graphics (CG) in order to generate visual representation of a new scene. Such CG systems may also implement various visual effects in the generated scene in order to illustrate certain types of motion. However, CG related systems generally create a scene, which is not photorealistic. In other words, such systems do not use photographic images as the main source of data from which to produce the output image of the scene.
As such, none of the existing imaging systems described above addresses the problem of identifying and isolating a moving foreground object from a sequence of photographic-quality images. Also, none of these systems have addressed the problem of, given a series of digital photographic images of a moving object, creating a new image containing a sharp representation of the object while conveying the appearance of motion by blurring the background. Furthermore, existing systems generally assume that the input sequence of images are already co-registered which will never be the case for images acquired using a handheld digital camera.